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Eingeladener Vortrag
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Safety and security both entail freedom from danger, i.e. unacceptable risk, whatever the cause might be. This
entails an understanding of the term 'risk' that is broadly used in areas such as economics, health, insurance etc.
According a rather popular definition used in the economical sciences for a long time (KNIGHT), risk has a lot
in common with uncertainty while the former is regarded quantifiable and the latter one is not. However, it has
to be taken into account that there are other understandings of 'uncertainty'. Particularly encountering rare
events never experienced before and recent contemporary definitions are weakening Knightfs differentiation.
This is reflected in some recent standard definitions. Attempts have been made to define a risk as common as
possible covering not only societal, ecological and financial areas but also natural and technical, ones. This is of
particular concern in non-destructive testing. This raises the question how far this can be achieved in a common
understanding, i.e. the discussion on this term seems not at all finished yet.
It is a common ambition to lower the risk by several actions including detection technologies. This entails that a
risk could be estimated somehow. The existence of numerous approaches indicates the complexity of this question.
The EFNDT (European Federation for Non-Destructive Testing) Working Group 5 took a commitment
also to tackle this central aspect of safety and security in its understanding as a bridging forum between these
two areas.
Stochastic artefacts are frequently encountered in digital radiography and tomography with neutrons. Most obviously, they are caused by ubiquitous scattered radiation hitting the CCD-sensor. They appear as scattered dots and, at higher frequency of occurrence, they may obscure the image. Some of these dotted interferences vary with time, however, a large portion of them remains persistent so the problem cannot be resolved by collecting stacks of images and to merge them to a median image. The situation becomes even worse in computed tomography (CT) where each artefact causes a circular pattern in the reconstructed plane. Therefore, these stochastic artefacts have to be removed completely and automatically while leaving the original image content untouched. A simplified image acquisition and artefact removal tool was developed at BAM and is available to interested users. Furthermore, an algorithm complying with all the requirements mentioned above was developed that reliably removes artefacts that could even exceed the size of a single pixel without affecting other parts of the image. It consists of an iterative two-step algorithm adjusting pixel values within a 3 × 3 matrix inside of a 5 × 5 kernel and the centre pixel only within a 3 × 3 kernel, resp. It has been applied to thousands of images obtained from the NECTAR facility at the FRM II in Garching, Germany, without any need of a visual control. In essence, the procedure consists of identifying and tackling asymmetric intensity distributions locally with recording each treatment of a pixel. Searching for the local asymmetry with subsequent correction rather than replacing individually identified pixels constitutes the basic idea of the algorithm. The efficiency of the proposed algorithm is demonstrated with a severely spoiled example of neutron radiography and tomography as compared with median filtering, the most convenient alternative approach by visual check, histogram and power spectra analysis.